Initial Questions to Explore

Will want to view all elk, antlered, antlerless, and the ratio of each for insights into these questions.

NOTICE that I am only looking at the general rifle hunting seasons on public land. There are also Harvest in Archery, Muzzleloader, Private Land, Ranching for Wildlife, etc.

Setup

setwd("~/_code/colorado-dow/Phase I - Descriptive Analytics")

Load required libraries for wrangling data, charting, and mapping

library(plyr,quietly = T) # data wrangling
library(dplyr,quietly = T) # data wrangling
library(ggplot2, quietly = T) # charting
library(ggthemes,quietly = T) # so I can add the highcharts theme and palette
library(scales,quietly = T) # to load the percent function when labeling plots

Set our preferred charting theme

theme_set(theme_minimal()+theme_hc())

Run script to get harvest data

source('~/_code/colorado-dow/datasets/Colorado Elk Harvest Data.R', echo=F)

Table of the harvest data

COElkRifleAll
source('~/_code/colorado-dow/datasets/Colorado GMUnit and Road data.R', echo=F)
## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/psarnow/_code/colorado-dow/datasets/CPW_GMUBoundaries/BigGameGMUBoundaries03172015.shp", layer: "BigGameGMUBoundaries03172015"
## with 185 features
## It has 12 fields
## Integer64 fields read as strings:  GMUID 
## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/psarnow/_code/colorado-dow/datasets/ne_10m_roads/ne_10m_roads.shp", layer: "ne_10m_roads"
## with 56601 features
## It has 29 fields
## Integer64 fields read as strings:  scalerank question

Take a peak at the boundary data

head(Unitboundaries2)

Total Elk Harvest

Statewide

# Group seasons
COElkHarvestStatewide <- summarise(group_by(COElkRifleAll,Year,Unit),
                                   Harvest = sum(c(Harvest.Antlered,Harvest.Antlerless),na.rm = T))
# Group Units
COElkHarvestStatewide <- summarise(group_by(COElkHarvestStatewide,Year),
                                   Harvest = sum(Harvest))

ggplot(COElkHarvestStatewide, aes(Year,Harvest)) +
  geom_bar(stat="identity",fill=ggthemes_data$hc$palettes$default[2]) +
  coord_cartesian(ylim = c(20000,35000)) +
  labs(title="Statewide Elk Harvest", caption="source: cpw.state.co.us")

TODO commentary

Harvest by Unit

How the Harvest is distributed across the state.

# Group seasons
COElkUnitHarvest <- summarise(group_by(COElkRifleAll,Year,Unit),
                              Harvest = sum(c(Harvest.Antlered,Harvest.Antlerless),na.rm = T))

Last year’s data

Year2017 <- filter(COElkUnitHarvest, Year == "2017")
HarvesttoPlot <- left_join(Unitboundaries2,Year2017, by=c("Unit"))
ggplot(HarvesttoPlot, aes(long, lat, group = group)) + 
  geom_polygon(aes(fill = Harvest),colour = "grey50", size = .2) + #Unit boundaries
  geom_path(data = COroads,aes(x = long, y = lat, group = group), color="#3878C7",size=2) + #Roads
  geom_text(data=data_centroids,aes(x=longitude,y=latitude,label = Unit),size=3) + #Unit labels
  scale_fill_distiller(palette = "Reds",direction = 1,na.value = 'light grey') +
  xlab("") + ylab("") +
  labs(title="2017 Colorado Elk Harvest", caption="source: cpw.state.co.us")

TODO - commentary

Harvest Rank of the Units

Would also be beneficial to rank each unit so I can reference later. In this case average the Harvest of the last few years

HarvestRanklast3 <- filter(COElkUnitHarvest, as.numeric(Year) >= 2015)
HarvestRanklast3 <- summarise(group_by(HarvestRanklast3,Unit),
                             Harvest = mean(Harvest,na.rm = T))
HarvestRanklast3$HarvestRank = rank(-HarvestRanklast3$Harvest)

HarvestRanklast3 <- filter(HarvestRanklast3, HarvestRank <= 50) # top 50 units

In order for the chart to retain the order of the rows, the X axis variable (i.e. the categories) has to be converted into a factor.

HarvestRanklast3 <- HarvestRanklast3[order(-HarvestRanklast3$Harvest), ]  # sort
HarvestRanklast3$Unit <- factor(HarvestRanklast3$Unit, levels = HarvestRanklast3$Unit)  # to retain the order in plot.

Lollipop Chart

ggplot(HarvestRanklast3, aes(x=Unit, y=Harvest)) + 
  geom_point(size=3) + 
  geom_segment(aes(x=Unit, 
                   xend=Unit, 
                   y=0, 
                   yend=Harvest)) + 
  labs(title="Average Elk Harvest 2015-2017\nTop 50 Units", subtitle="Harvest by Unit", caption="source: cpw.state.co.us")

TODO - commentary

Antlered Elk Harvest

Statewide

# Group seasons
COElkAntHarvestStatewide <- summarise(group_by(COElkRifleAll,Year,Unit),
                                   Antlered_Harvest = sum(c(Harvest.Antlered),na.rm = T))
# Group Units
COElkAntHarvestStatewide <- summarise(group_by(COElkAntHarvestStatewide,Year),
                                      Antlered_Harvest = sum(Antlered_Harvest))

ggplot(COElkAntHarvestStatewide, aes(Year,Antlered_Harvest)) +
  geom_bar(stat="identity",fill=ggthemes_data$hc$palettes$default[1]) +
  coord_cartesian(ylim = c(10000,20000)) +
  labs(title="Statewide Antlered Elk Harvest", caption="source: cpw.state.co.us")

TODO commentary

Antlered Harvest by Unit

How the Antlered Harvest is distributed across the state.

# Group seasons
COElkUnitAntHarvest <- summarise(group_by(COElkRifleAll,Year,Unit),
                              Antlered_Harvest = sum(c(Harvest.Antlered),na.rm = T))

Last year’s data

Year2017 <- filter(COElkUnitAntHarvest, Year == "2017")
HarvesttoPlot <- left_join(Unitboundaries2,Year2017, by=c("Unit"))
ggplot(HarvesttoPlot, aes(long, lat, group = group)) + 
  geom_polygon(aes(fill = Antlered_Harvest),colour = "grey50", size = .2) + #Unit boundaries
  geom_path(data = COroads,aes(x = long, y = lat, group = group), color="#3878C7",size=2) + #Roads
  geom_text(data=data_centroids,aes(x=longitude,y=latitude,label = Unit),size=3) + #Unit labels
  scale_fill_distiller(palette = "Blues",direction = 1,na.value = 'light grey') +
  xlab("") + ylab("") +
  labs(title="2017 Colorado Antlered Elk Harvest", caption="source: cpw.state.co.us")

TODO - commentary

Antlered Harvest Rank of the Units

Would also be beneficial to rank each unit so I can reference later. In this case average the Antlered Harvest of the last few years

AntHarvestRanklast3 <- filter(COElkUnitAntHarvest, as.numeric(Year) >= 2015)
AntHarvestRanklast3 <- summarise(group_by(AntHarvestRanklast3,Unit),
                                 Antlered_Harvest = mean(Antlered_Harvest,na.rm = T))
AntHarvestRanklast3$HarvestRank = rank(-AntHarvestRanklast3$Antlered_Harvest)

AntHarvestRanklast3 <- filter(AntHarvestRanklast3, HarvestRank <= 50) # top 50 units

In order for the chart to retain the order of the rows, the X axis variable (i.e. the categories) has to be converted into a factor.

AntHarvestRanklast3 <- AntHarvestRanklast3[order(-AntHarvestRanklast3$Antlered_Harvest), ]  # sort
AntHarvestRanklast3$Unit <- factor(AntHarvestRanklast3$Unit, levels = AntHarvestRanklast3$Unit)  # to retain the order in plot.

Lollipop Chart

ggplot(AntHarvestRanklast3, aes(x=Unit, y=Antlered_Harvest)) + 
  geom_point(size=3) + 
  geom_segment(aes(x=Unit, 
                   xend=Unit, 
                   y=0, 
                   yend=Antlered_Harvest)) + 
  labs(title="Average Antlered Elk Harvest 2015-2017\nTop 50 Units", subtitle="Harvest by Unit", caption="source: cpw.state.co.us")

TODO - commentary

Antlerless Elk Harvest

Statewide

# Group seasons
COElkAntlessHarvestStatewide <- summarise(group_by(COElkRifleAll,Year,Unit),
                                      Antlerless_Harvest = sum(c(Harvest.Antlerless),na.rm = T))
# Group Units
COElkAntlessHarvestStatewide <- summarise(group_by(COElkAntlessHarvestStatewide,Year),
                                      Antlerless_Harvest = sum(Antlerless_Harvest))

ggplot(COElkAntlessHarvestStatewide, aes(Year,Antlerless_Harvest)) +
  geom_bar(stat="identity",fill=ggthemes_data$hc$palettes$default[3]) +
  # coord_cartesian(ylim = c(10000,20000)) +
  labs(title="Statewide Antlerless Elk Harvest", caption="source: cpw.state.co.us")

TODO commentary

Antlerless Harvest by Unit

How the Antlerless Harvest is distributed across the state.

# Group seasons
COElkUnitAntlessHarvest <- summarise(group_by(COElkRifleAll,Year,Unit),
                                 Antlerless_Harvest = sum(c(Harvest.Antlerless),na.rm = T))

Last year’s data

Year2017 <- filter(COElkUnitAntlessHarvest, Year == "2017")
HarvesttoPlot <- left_join(Unitboundaries2,Year2017, by=c("Unit"))
ggplot(HarvesttoPlot, aes(long, lat, group = group)) + 
  geom_polygon(aes(fill = Antlerless_Harvest),colour = "grey50", size = .2) + #Unit boundaries
  geom_path(data = COroads,aes(x = long, y = lat, group = group), color="#3878C7",size=2) + #Roads
  geom_text(data=data_centroids,aes(x=longitude,y=latitude,label = Unit),size=3) + #Unit labels
  scale_fill_distiller(palette = "Greens",direction = 1,na.value = 'light grey') +
  xlab("") + ylab("") +
  labs(title="2017 Colorado Antlerless Elk Harvest", caption="source: cpw.state.co.us")

TODO - commentary

Antlerless Harvest Rank of the Units

Would also be beneficial to rank each unit so I can reference later. In this case average the Antlerless Harvest of the last few years

AntlessHarvestRanklast3 <- filter(COElkUnitAntlessHarvest, as.numeric(Year) >= 2015)
AntlessHarvestRanklast3 <- summarise(group_by(AntlessHarvestRanklast3,Unit),
                                 Antlerless_Harvest = mean(Antlerless_Harvest,na.rm = T))
AntlessHarvestRanklast3$HarvestRank = rank(-AntlessHarvestRanklast3$Antlerless_Harvest)

AntlessHarvestRanklast3 <- filter(AntlessHarvestRanklast3, HarvestRank <= 50) # top 50 units

In order for the chart to retain the order of the rows, the X axis variable (i.e. the categories) has to be converted into a factor.

AntlessHarvestRanklast3 <- AntlessHarvestRanklast3[order(-AntlessHarvestRanklast3$Antlerless_Harvest), ]  # sort
AntlessHarvestRanklast3$Unit <- factor(AntlessHarvestRanklast3$Unit, levels = AntlessHarvestRanklast3$Unit)  # to retain the order in plot.

Lollipop Chart

ggplot(AntlessHarvestRanklast3, aes(x=Unit, y=Antlerless_Harvest)) + 
  geom_point(size=3) + 
  geom_segment(aes(x=Unit, 
                   xend=Unit, 
                   y=0, 
                   yend=Antlerless_Harvest)) + 
  labs(title="Average Antlerless Elk Harvest 2015-2017\nTop 50 Units", subtitle="Harvest by Unit", caption="source: cpw.state.co.us")

TODO - commentary

Conclusion

TODO - commentary and follow up questions